VP of Engineering
Skills
About the Role
You will own the end-to-end migration from a legacy stack to an AI-native data pipeline and ensure production readiness without disrupting customer SLAs. You will drive architectural decisions, sequence service cutovers, and validate parallel runs. You will restore platform performance by reducing latency and database load, fixing stability regressions, and increasing release cadence. You will establish clear accountability across squad leads and managers, make hiring and performance decisions, and improve engineering management practices. You will build shared AI-assisted engineering infrastructure including code generation, automated testing, and agent-based migration tooling. You will translate engineering investments into measurable customer outcomes, manage the engineering budget, and communicate risks and progress to executives.
Requirements
- 10+ years engineering experience with 5+ years leading platform data or infrastructure organizations as VP Engineering Head of Engineering or equivalent
- Led at least one major platform migration or large-scale rebuild while maintaining continuous customer service
- Operated low-latency high-availability distributed systems with multi-tenant SaaS workloads at production scale
- Production experience integrating AI into engineering workflows including agent-assisted development and AI-driven automation
- Strong product partnership instincts
- Track record of building accountable high-ownership engineering organizations
- Direct experience in one or more domains: blockchain crypto fintech payments fraud risk platforms regulatory technology or large-scale data platforms
Responsibilities
- Own the platform migration end-to-end
- Integrate the new data pipeline into all products
- Sequence migrations to preserve revenue and customer SLAs
- Drive architectural decisions and trade-offs for cutover
- Align engineering product and customer success on a single migration roadmap
- Restore API and core platform latency to target
- Reduce database load and fix stability regressions
- Increase release velocity to multiple deployments per week
- Lead multi-chain platform integrations across 100+ chains
- Establish accountability across squad leads and engineering managers
- Make hiring performance and structural decisions for the engineering organization
- Build shared AI-assisted engineering infrastructure
- Deploy organization-wide AI productivity tools
- Reduce operational expense through automation and architectural improvements
- Translate engineering investments into customer outcomes and revenue
- Own the engineering budget and vendor decisions